Expert Systems

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this presentation provides an introduction to the expert systems.

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  • Expert Systems

    1. 1. EXPERT SYSTEMS BY MEHWISH MANZER (63) MEER SADAF NAEEM (58) DUR-E-MALIKA (55)
    2. 2. Overview <ul><li>What is an Expert System? </li></ul><ul><li>History </li></ul><ul><li>Components of Expert System </li></ul><ul><li>Who is involved? </li></ul><ul><li>Development of Expert System </li></ul>
    3. 3. WHAT IS AN EXPERT SYSTEM? <ul><li>An expert system is a computer program that contains some of the subject-specific knowledge of one or more human experts. </li></ul>
    4. 4. History of Expert Systems
    5. 5. <ul><li>Early 70s </li></ul><ul><li>Goal of AI scientists  develop computer programs that could in some sense think . </li></ul><ul><li>In 60s  general purpose programs were developed for solving the classes of problems but this strategy produced no breakthroughs. </li></ul><ul><li>In 1970  it was realized that The problem-solving power of program comes from the knowledge it possesses. </li></ul>
    6. 6. To make a program intelligent, provide it with lots of high-quality, specific knowledge about some problem area.
    7. 7. Building Blocks of Expert System
    8. 8. <ul><li>Knowledge base (facts) </li></ul><ul><li>Production Rules (&quot;if.., then..&quot;) </li></ul><ul><li>Inference Engine (controls how &quot;if.., then..&quot; rules are applied towards facts) </li></ul><ul><li>User Interface </li></ul>
    9. 9. Knowledge Base <ul><li>The component of an expert system that contains the system’s knowledge. </li></ul><ul><li>Expert systems are also known as Knowledge-based systems. </li></ul>
    10. 10. Knowledge Representation <ul><li>Knowledge is represented in a computer in the form of rules ( Production rule). </li></ul><ul><li>Consists of an IF part and THEN part. </li></ul><ul><li>IF part lists a set of conditions in some logical combination. </li></ul><ul><li>If the IF part of the rule is satisfied; consequently, the THEN part can be concluded. </li></ul>
    11. 11. Knowledge Representation <ul><li>If flammable liquid was spilled then call the fire department. </li></ul><ul><li>If the material is acid and smells like vinegar then the spill material is acetic acid. </li></ul>
    12. 12. <ul><li>Chaining of IF-THEN rules to form a line of reasoning </li></ul><ul><li>Forward chaining (facts driven) </li></ul><ul><li>Backward chaining (goal driven) </li></ul>
    13. 13. Inference Engine <ul><li>An inference engine tries to derive answers from a knowledge base. </li></ul><ul><li>It is the brain of the expert systems that provides a methodology for reasoning about the information in the knowledge base, and for formulating conclusions. </li></ul>
    14. 14. User Interface <ul><li>It enables the user to communicate with an expert system. </li></ul>
    15. 15. Other features <ul><li>Reasoning with uncertainty </li></ul><ul><li>Explanation of the line of reasoning </li></ul><ul><li>Fuzzy Logic </li></ul>
    16. 16. Who is involved? ?
    17. 17. Knowledge Engineer <ul><li>A knowledge engineer is a computer scientist who knows how to design and implement programs that incorporate artificial intelligence techniques. </li></ul>
    18. 18. Domain Expert <ul><li>A domain expert is an individual who has significant expertise in the domain of the expert system being developed. </li></ul>
    19. 19. Knowledge Engineering <ul><li>The art of designing and building the expert systems is known as KNOWLEDGE ENGINEERING knowledge engineers are its practitioners. </li></ul><ul><li>Knowledge engineering relies heavily on the study of human experts in order to develop intelligent & skilled programs. </li></ul>
    20. 20. Developing Expert Systems <ul><li>Determining the characteristics of the problem. </li></ul><ul><li>Knowledge engineer and domain expert work together closely to describe the problem. </li></ul>
    21. 21. <ul><li>The engineer then translates the knowledge into a computer-usable language, and designs an inference engine, a reasoning structure, that uses the knowledge appropriately. </li></ul><ul><li>He also determines how to integrate the use of uncertain knowledge in the reasoning process, and what kinds of explanation would be useful to the end user. </li></ul>
    22. 22. <ul><li>When the expert system is implemented, it may be: </li></ul><ul><ul><ul><li>The inference engine is not just right </li></ul></ul></ul><ul><ul><ul><li>Form of representation of knowledge is awkward </li></ul></ul></ul><ul><li>An expert system is judged to be entirely successful when it operates on the level of a human expert. </li></ul>
    23. 23. Human Expertise vs Artificial Expertise <ul><li>Perishable </li></ul><ul><li>Difficult to transfer </li></ul><ul><li>Difficult to document </li></ul><ul><li>Unpredictable </li></ul><ul><li>Expensive </li></ul><ul><li>Permanent </li></ul><ul><li>Easy to transfer </li></ul><ul><li>Easy to document </li></ul><ul><li>Consistent </li></ul><ul><li>Affordable </li></ul>
    24. 24. Some Prominent Expert Systems <ul><li>Dendral </li></ul><ul><li>Dipmeter Advisor </li></ul><ul><li>Mycin </li></ul><ul><li>R1/Xcon </li></ul>
    25. 25. THE END THANK YOU

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